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Co-authored-by: Loïck BOURDOIS <[email protected]>

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- ---
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- license: apache-2.0
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- ---
 
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- HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022).
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-
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- The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in the original github repo.
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-
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- * Note: due to the difference between the implementations of the original Longformer and the Huggingface LED model, the results of converted models are slightly different. We run a sanity check on both fine-tuned and non fine-tuned models on the **MultiNews dataset**, and show the results below:
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-
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- | Model | Rouge-1 | Rouge-2 | Rouge-L |
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- | --- | ----------- |----------- |----------- |
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- | PRIMERA | 42.0 | 13.6 | 20.8|
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- | PRIMERA-hf | 41.7 |13.6 | 20.5|
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- | PRIMERA(finetuned) | 49.9 | 21.1 | 25.9|
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- | PRIMERA-hf(finetuned) | 49.9 | 20.9 | 25.8|
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-
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- You can use it by
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- ```
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- from transformers import (
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- AutoTokenizer,
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- LEDConfig,
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- LEDForConditionalGeneration,
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- )
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- tokenizer = AutoTokenizer.from_pretrained('allenai/PRIMERA')
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- config=LEDConfig.from_pretrained('allenai/PRIMERA')
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- model = LEDForConditionalGeneration.from_pretrained('allenai/PRIMERA')
 
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  ```
 
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+ ---
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+ language: en
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+ license: apache-2.0
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+ ---
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+
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+ HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022).
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+
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+ The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in the original github repo.
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+
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+ * Note: due to the difference between the implementations of the original Longformer and the Huggingface LED model, the results of converted models are slightly different. We run a sanity check on both fine-tuned and non fine-tuned models on the **MultiNews dataset**, and show the results below:
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+
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+ | Model | Rouge-1 | Rouge-2 | Rouge-L |
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+ | --- | ----------- |----------- |----------- |
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+ | PRIMERA | 42.0 | 13.6 | 20.8|
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+ | PRIMERA-hf | 41.7 |13.6 | 20.5|
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+ | PRIMERA(finetuned) | 49.9 | 21.1 | 25.9|
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+ | PRIMERA-hf(finetuned) | 49.9 | 20.9 | 25.8|
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+
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+ You can use it by
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+ ```
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+ from transformers import (
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+ AutoTokenizer,
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+ LEDConfig,
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+ LEDForConditionalGeneration,
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained('allenai/PRIMERA')
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+ config=LEDConfig.from_pretrained('allenai/PRIMERA')
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+ model = LEDForConditionalGeneration.from_pretrained('allenai/PRIMERA')
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  ```